Solutions Architect - Emerging Enterprise (startups)

Databricks Databricks · Data AI · San Francisco, CA · Field Engineering

Solutions Architect for Databricks, focusing on emerging enterprise clients. This role involves leading customer adoption of the Databricks Unified Analytics Platform, consulting on big data architecture, implementing proof of concepts for data science and machine learning projects, and guiding customers through implementations. The role requires technical leadership, strong communication skills, and expertise in data engineering, data analytics, data science, and machine learning technologies, with a focus on open-source projects like Apache Spark, MLflow, and Delta Lake.

What you'd actually do

  1. Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
  2. Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
  3. Build and present reference architectures, technical guides, and demo applications for customers
  4. Provide escalated support for critical customer operational issues
  5. Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars

Skills

Required

  • 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
  • Experience designing and architecting distributed data systems
  • Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
  • Have built solutions with public cloud providers, such as AWS, Azure, or GCP
  • Experience in at least one of the following: Data Engineering technologies (e.g., Spark, Hadoop, Kafka), Data Warehousing (e.g., SQL, OLTP/OLAP/DSS), Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)

Nice to have

  • Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
  • Databricks Certification

What the JD emphasized

  • customer-facing
  • technical architecture
  • Data Science and Machine Learning technologies

Other signals

  • customer-facing
  • technical leadership
  • architectures and solutions
  • implement proof of concepts
  • data science and machine learning projects